{"title":"Mobile Health Mashups: Making sense of multiple streams of wellbeing and contextual data for presentation on a mobile device","authors":"Konrad Tollmar, Frank Bentley, Cristobal Viedma","doi":"10.4108/ICST.PERVASIVEHEALTH.2012.248698","DOIUrl":null,"url":null,"abstract":"In this paper we present the Mobile Health Mashups system, a mobile service that collects data from a variety of health and wellbeing sensors and presents significant correlations across sensors in a mobile widget as well as on a mobile web application. We found that long-term correlation data provided users with new insights about systematic wellness trends that they could not make using only the time series graphs provided by the sensor manufacturers. We describe the Mobile Health Mashups system with a focus on analyzing and detailing the technical solution, such as: integration of sensors, how to create correlations between various data sets, and the presentation of the statistical data as feeds and graphs. We will also describe the iterative design process that involved a 2-month field trial, the outcome of this trial, and implications for design of mobile data mashup systems.","PeriodicalId":119950,"journal":{"name":"2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"57","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/ICST.PERVASIVEHEALTH.2012.248698","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 57
Abstract
In this paper we present the Mobile Health Mashups system, a mobile service that collects data from a variety of health and wellbeing sensors and presents significant correlations across sensors in a mobile widget as well as on a mobile web application. We found that long-term correlation data provided users with new insights about systematic wellness trends that they could not make using only the time series graphs provided by the sensor manufacturers. We describe the Mobile Health Mashups system with a focus on analyzing and detailing the technical solution, such as: integration of sensors, how to create correlations between various data sets, and the presentation of the statistical data as feeds and graphs. We will also describe the iterative design process that involved a 2-month field trial, the outcome of this trial, and implications for design of mobile data mashup systems.
在本文中,我们介绍了移动健康mashup系统,这是一种从各种健康和福祉传感器收集数据的移动服务,并在移动小部件和移动web应用程序中呈现传感器之间的显著相关性。我们发现,长期相关数据为用户提供了关于系统健康趋势的新见解,这是他们仅使用传感器制造商提供的时间序列图所无法做到的。我们将介绍Mobile Health Mashups系统,重点分析和详细介绍技术解决方案,例如:传感器的集成、如何在各种数据集之间创建相关性,以及将统计数据表示为提要和图表。我们还将描述涉及2个月现场试验的迭代设计过程、试验结果以及对移动数据混搭系统设计的影响。